DESIGN AND DEVELOPMENT OF AN ATTACK-RESISTANT IOT CLOUD CONVERGENCE ALGORITHM USING ATTRIBUTE-BASED ENCRYPTION

As the number of Internet of Things (IoT) devices grows quickly, it becomes harder to keep data handling and communication safe in cloud settings. This paper describes how an attack-proof IoT cloud convergence method was designed and built. It uses Ciphertext-Policy Attribute-Based Encryption (CP-ABE) to provide strong security and fine-grained, attribute-based access control. The suggested framework uses CP-ABE based on the Bethencourt-Sahai-Waters (BSW) method to make key generation, sharing, encryption, and decoding safe and user-attribute-aligned. This makes sure that only authorised users can access critical data. To make sure the encryption is strong and works well, the method uses the JPBC library to perform pairing-based cryptography processes. Using attribute-based registration and login, the user module makes sure that users are who they say they are and that they have the right permissions. The system handles files by encrypting them with lightweight AES for privacy, hashing them with SHA-256 for integrity checks, and letting you securely share and download files with reporting support. The Third Party Auditor (TPA) tool also makes sure that files are real and manages user termination to stop people from getting in without permission after a key has been compromised or a characteristic has been changed. A performance study shows that the suggested method works by comparing how much time and memory are used for decrypting both insourced and outsourced files of different sizes. The results show that the system strikes a good balance between security and speed. This means that it can be used in real-life IoT-cloud situations where resources are limited and changing access control is important. The comparison study shows that attribute-based encryption is better at protecting against different types of threats while still having a reasonable amount of extra work to do.

Authors

Publication Details

Journal
International Journal of Apllied Mathematics
Published
2025-09-09
DOI
https://doi.org/10.12732/ijam.v38i1s.5
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DESIGN AND DEVELOPMENT OF AN ATTACK-RESISTANT IOT CLOUD CONVERGENCE ALGORITHM USING ATTRIBUTE-BASED ENCRYPTION

Deepak Sapkal
International Journal of Apllied Mathematics
Chaos-based Image/Signal Encryption
article

DESIGN AND DEVELOPMENT OF AN ATTACK-RESISTANT IOT CLOUD CONVERGENCE ALGORITHM USING ATTRIBUTE-BASED ENCRYPTION

Deepak Sapkal
article en

Abstract

As the number of Internet of Things (IoT) devices grows quickly, it becomes harder to keep data handling and communication safe in cloud settings. This paper describes how an attack-proof IoT cloud convergence method was designed and built. It uses Ciphertext-Policy Attribute-Based Encryption (CP-ABE) to provide strong security and fine-grained, attribute-based access control. The suggested framework uses CP-ABE based on the Bethencourt-Sahai-Waters (BSW) method to make key generation, sharing, encryption, and decoding safe and user-attribute-aligned. This makes sure that only authorised users can access critical data. To make sure the encryption is strong and works well, the method uses the JPBC library to perform pairing-based cryptography processes. Using attribute-based registration and login, the user module makes sure that users are who they say they are and that they have the right permissions. The system handles files by encrypting them with lightweight AES for privacy, hashing them with SHA-256 for integrity checks, and letting you securely share and download files with reporting support. The Third Party Auditor (TPA) tool also makes sure that files are real and manages user termination to stop people from getting in without permission after a key has been compromised or a characteristic has been changed. A performance study shows that the suggested method works by comparing how much time and memory are used for decrypting both insourced and outsourced files of different sizes. The results show that the system strikes a good balance between security and speed. This means that it can be used in real-life IoT-cloud situations where resources are limited and changing access control is important. The comparison study shows that attribute-based encryption is better at protecting against different types of threats while still having a reasonable amount of extra work to do.

International Journal of Apllied MathematicsVol. 38(1s)
Openalex Percentile: Top 75%
Chaos-based Image/Signal Encryption
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.